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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Deep learning of interface structures from simulated 4D STEM data: cation intermixing vs. roughening ∗

Abstract Interface structures in complex oxides remain an active area of condensed matter physics research, largely enabled by recent advances in scanning transmission electron microscopy (STEM). Yet the nature of the STEM contrast in which the structure is projected along the given direction precludes separation of possible structural models. Here, we utilize deep convolutional neural networks (DCNN) trained on simulated 4D STEM datasets to predict structural descriptors of interfaces. We focus on the widely studied interface between LaAlO 3 and SrTiO 3 , using dynamical diffraction theory and leveraging high performance computing to simulate thousands of possible 4D STEM datasets to train the DCNN to learn properties of the underlying structures on which the simulations are based. We test the DCNN on simulated data and show that it is possible (with >95% accuracy) to identify a physically rough from a chemically diffuse interface and create a DCNN regression model to predict step positions. We quantify the applicability of the model to different thicknesses and the transferability of the approach. The method shown here is general and can be applied for any inverse imaging problem where forward models are present.

42 ENGINEERING↗
DOE OSTI2025

Reactor System Facility Modification to Detect Compromised Human Machine Interfaces

This study focuses on a multi-layered Industrial Control System (ICS)/Operational Technology (OT) security architecture to aid in the discovery and mitigation of compromised Human Machine Interface (HMI)/Instrumentation & Control (I&C) based systems for modifying a prototypical reactor condition test facility called the Flowing Autoclave System (FAS) at Idaho National Laboratory (INL). This is achieved through a three-layered combination of network security solutions, hash-based algorithms, and blockchain technologies. Hash algorithms are mathematical functions used to generate a predetermined set of fixed-length values. They are widely used in computer security to verify the integrity of system information and data, both on a local network and the wider internet. Even small amounts of unauthorized system modification will cause the hash algorithm to output a set of characters that deviate significantly from its original value. Assisting secure hash functions, blockchain technology is a secure and distributed technology used to provide an immutable set of records replicated on all devices within a decentralized network. Blockchain offers a cost-effective solution to detect system compromise by providing a traceable breadcrumb trail of all network activity and data modification happening on a system. If both are used in conjunction with network monitoring tools, the integration of this three-pronged approach can become an asset in detecting suspected system compromises before any real damage can occur.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Computational Investigation of Aqueous Phase Effects on the Dehydrogenation and Dehydroxylation of Polyols over Pt(111)

Prediction of solvation effects on the kinetics of elementary reactions occurring at metal–water interfaces is of high importance for the rational design of catalysts for the biomass and electrocatalysis communities. A lack of knowledge of the reliability of various computational solvation schemes for processes on metal surfaces is currently a limiting factor. Using a multilevel quantum mechanical/molecular mechanical (QM/MM) description of the potential energy surface, we determined characteristic time and length scales for typical free-energy perturbation (FEP) calculations of bond cleavages in ethylene glycol, a sugar surrogate molecule, over Pt(111). Our approach is based on our explicit solvation model for metal surfaces and the repetition of FEP calculations to estimate confidence intervals. Results indicate that aqueous phase effects on the free energies of elementary processes can be determined with 95% confidence intervals from limited configuration space sampling and the fixed charge approximation used in the QM/MM-FEP methodology of smaller 0.1 eV. Next, we computed the initial O–H, C–H, and C–OH bond cleavages in ethylene glycol over Pt(111) in liquid water utilizing two different metal–water interaction potentials. Our calculations predict that aqueous phase effects are small (<0.1 eV) for the C–H bond cleavage and the activation barrier of the C–OH bond cleavage. In contrast, solvation effects are large (>0.35 eV) for the O–H bond cleavage and the reaction free energy of the C–OH bond scission. While the choice of a different Pt–water force field can lead to differences in predicted solvation effects of up to 0.2 eV, the differences are usually smaller (<0.1 eV), and the trends are always the same. In contrast, implicit solvation methods appear to currently not be able to reliably describe solvation effects originating from hydrogen bonding for metal surfaces even qualitatively.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Petascale supercomputing to accelerate the design of high-temperature alloys

Recent progress in high-performance computing and data informatics has opened up numerous opportunities to aid the design of advanced materials. Herein, we demonstrate a computational workflow that includes rapid population of high-fidelity materials datasets via petascale computing and subsequent analyses with modern data science techniques. We use a first-principles approach based on density functional theory to derive the segregation energies of 34 microalloying elements at the coherent and semi-coherent interfaces between the aluminium matrix and the θ '-Al 2 Cu precipitate, which requires several hundred supercell calculations. We also perform extensive correlation analyses to identify materials descriptors that affect the segregation behaviour of solutes at the interfaces. Finally, we show an example of leveraging machine learning techniques to predict segregation energies without performing computationally expensive physics-based simulations. As a result, the approach demonstrated in the present work can be applied to any high-temperature alloy system for which key materials data can be obtained using high-performance computing.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Prediction of hydration energies of adsorbates at Pt(111) and liquid water interfaces using machine learning

Aqueous phase heterogeneous catalysis is important to various industrial processes, including biomass conversion, Fischer–Tropsch synthesis, and electrocatalysis. Accurate calculation of solvation thermodynamic properties is essential for modeling the performance of catalysts for these processes. Explicit solvation methods employing multiscale modeling, e.g., involving density functional theory and molecular dynamics have emerged for this purpose. Although accurate, these methods are computationally intensive. This study introduces machine learning (ML) models to predict solvation thermodynamics for adsorbates on a Pt(111) surface, aiming to enhance computational efficiency without compromising accuracy. In particular, ML models are developed using a combination of molecular descriptors and fingerprints and trained on previously published water–adsorbate interaction energies, energies of solvation, and free energies of solvation of adsorbates bound to Pt(111). These models achieve root mean square error values of 0.09 eV for interaction energies, 0.04 eV for energies of solvation, and 0.06 eV for free energies of solvation, demonstrating accuracy within the standard error of multiscale modeling. Feature importance analysis reveals that hydrogen bonding, van der Waals interactions, and solvent density, together with the properties of the adsorbate, are critical factors influencing solvation thermodynamics. Furthermore, these findings suggest that ML models can provide rapid and reliable predictions of solvation properties. This approach not only reduces computational costs but also offers insights into the solvation characteristics of adsorbates at Pt(111)–water interfaces.

Adsorption↗
DOE OSTI2024

A high-throughput and data-driven computational framework for novel quantum materials

Two-dimensional layered materials, such as transition metal dichalcogenides (TMDs), possess an intrinsic van der Waals gap at the layer interface, allowing for remarkable tunability of the optoelectronic features via external intercalation of foreign guests such as atoms, ions, or molecules. Herein, we introduce a high-throughput, data-driven computational framework for the design of novel quantum materials derived from intercalating planar conjugated organic molecules into bilayer transition metal dichalcogenides and dioxides. By combining first-principles methods, material informatics, and machine learning, we characterize the energetic and mechanical stability of this new class of materials and identify the fifty (50) most stable hybrid materials from a vast configurational space comprising ∼105 materials, employing intercalation energy as the screening criterion.

Kastuar, Srihari M. (ORCID:0000000279001561)↗
DOE OSTI2023

Grid Event Signature Library Analytics Report: Signature Matching Tool Development Efforts

This report describes the purpose and features of the Signature Matching Tool (SMT), employed in the Department of Energy (DOE) Grid Event Signature Library (GESL). The SMT supports a user of GESL to identify snippets of electric signatures, usually from sensor devices measuring electric characteristics such as phase voltages and currents, frequency, etc., suspected to represent certain events in the power grid but are not known to the user. The SMT uses a classification method to identify an event of the unknown signature, using the repository of known and labeled signatures in the GESL. The classifier applies a local binary classifier per node (LCN) approach to the unique event tag taxonomy used in the GESL, where training phases are separated based on the Primary labels in the taxonomy, sensor type, and voltage level. Results show that this method helps with computing time during training, in comparison to a flat, multinomial classifier, and produces acceptable average accuracy of 83% across all Primary labels. The report concludes with planned future work including integration to the web interface and API.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Investigation of radiation damage tolerance in interface-containing metallic nano structures

The proposed work seeks to conduct a basic study by applying experimental and computational methods to obtain quantitative influence of helium sink strength and proximity on He bubble nucleation and growth in He-irradiated nano-scale metallic structures, and the ensuing deformation mechanisms and mechanical properties. We utilized a combination of nano-scale in-situ tension and compression experiments on low-energy He-irradiated samples combined with site-specific microstructural characterization and modeling efforts. We also investigated the mechanical deformation of nano-architected materials, i.e. nanolattices which are comprised of 3-dimensional interwoven networks of hollow tubes, with the wall thickness in the nanometer range. This systematic approach will provide us with critical information for identifying key factors that govern He bubble nucleation and growth upon irradiation as a function of both sink strength and sink proximity through an experimentally-confirmed physical understanding. As an outgrowth of these efforts, we performed irradiations with self-ions (Ni 2+ ) on Ni-Al-Zr metallic glass nanolattices to assess their resilience against radiation damage rather than He-ion implantation. We focused our attention on studying individual bcc/fcc interfaces within a single nano structure (nano-pillar or a hollow tube): a single Fe (bcc)-Cu (fcc) boundary per pillar oriented perpendicular to the pillar axes, as well as pure bcc and fcc nano structures. Additional interfaces of interest include bcc/bcc and metal/metallic glass all within a single nano-structure volume. The model material systems are: (1) pure single crystalline Fe and Cu, (2) a single Fe (bcc)-Cu (fcc) boundary per nano structure (3) a single metal–metallic glass, all oriented non-parallel to the loading direction so that their fracture strength can be tested. A nano-fabrication approach, which involves e-beam lithography and templated electroplating, as well as two-photon lithography, was utilized, which enabled precise control of the initial microstructure control. Experimentally determined stress-strain relationships were enhanced by in-situ SEM observations coupled with TEM microstructural characterization of the same samples before and after deformation (irradiated and as-fabricated) and atomistic (MD) modeling. A comprehensive suite of experiments was conducted to quantitatively assess the key parameters for He bubble nucleation and growth by independently varying the sink strength, sink proximity, and He implantation temperature and dose. The implantations were conducted at Sandia and Los Alamos National Labs (CINT). Nano structuress containing He-enriched interfaces and irradiation-damaged microstructure were tested under uniaxial tension to assess embrittlement, resulting boundary strength, and deformation mechanisms. Results of this work helped identify which types of interfaces are particularly resilient against radiation damage.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Scalable Cloning on Large-Scale GPU Platforms with Application to Time-Stepped Simulations on Grids

Cloning is a technique to efficiently simulate a tree of multiple what-if scenarios that are unraveled during the course of a base simulation. However, cloned execution is highly challenging to realize on large, distributed memory computing platforms, due to the dynamic nature of the computational load across clones, and due to the complex dependencies spanning the clone tree. In this paper, we present the conceptual simulation framework, algorithmic foundations, and runtime interface of CloneX, a new system we designed for scalable simulation cloning. It efficiently and dynamically creates whole logical copies of a dynamic tree of simulations across a large parallel system without full physical duplication of computation and memory. The performance of a prototype implementation executed on up to 1,024 graphical processing units of a supercomputing system has been evaluated with three benchmarks—heat diffusion, forest fire, and disease propagation models—delivering a speed up of over two orders of magnitude compared to replicated runs. Finally, the results demonstrate a significantly faster and scalable way to execute many what-if scenario ensembles of large simulations via cloning using the CloneX interface.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Integrating DOE ASCR Computing into HEPCloud through GlideinWMS

Fermilab's HEPCloud facility expands the laboratory's computing capacity by provisioning resources beyond the local grid, using GlideinWMS to deliver pilots to where experiments such as CMS and DUNE run. The High-Performance Computing (HPC) facilities of the DOE Office of Advanced Scientific Computing Research (ASCR) are a growing part of that pool. HEPCloud currently provisions NERSC over SSH, but NERSC is moving away from that path as it adopts multi-factor authentication and directs automated access to its Superfacility API and the DOE Integrated Research Infrastructure (IRI) APIs. Maintaining and extending access across the ASCR ecosystem now requires provisioning through these interfaces. This work adds new pilot submission paths to GlideinWMS for the NERSC Superfacility API, IRI, and Globus Compute. Each uses the provisioning model GlideinWMS already applies to batch resources, so experiments can run on ASCR computing resources without changes to their existing workflows. This work finally presents a comparison of the paths to guide which interfaces are best suited for different workflows.

Majumder, Meghanto [U. Houston (main)]↗
DOE OSTI2018

DES science portal: Computing photometric redshifts

We present the Dark Energy Survey (DES) Science Portal, an integratedweb-based data interface designed to facilitate scientific analysis. Wedemonstrate how the Portal can provide a reliable environment to accesscomplete data sets, provide validation algorithms and metrics in the case ofmultiple methods and training configurations, and maintain the provenancebetween the different steps of a complex calculation, while ensuringreproducibility of the results. We use the estimation of DES photometricredshifts (photo-$z$s) as an example. A significant challenge facingphotometric surveys for cosmological purposes, such as DES, is the need toproduce reliable redshift estimates. The choice between competing algorithmsand configurations and the maintenance of an up-to-date spectroscopic databaseto build training sets, for example, are complex tasks when dealing with largeamounts of data that are regularly updated and constantly growing. We show howthe DES Science Portal can be used to train and validate several photo-$z$algorithms using the DES first year (Y1A1) data. The photo-$z$s estimated inthe Portal are used to feed the creation of catalogs for scientific workflows.While the DES collaboration is still developing techniques to obtain precisephoto-$z$s, having a structured framework like the one presented here iscritical for the systematic vetting of DES algorithmic improvements and theconsistent production of photo-$z$s in future DES releases.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Nuclear Materials Packaging, Transportation, and Systems Analysis Group Software Quality Assurance Plan: ANSYS Mechanical Finite Element Analysis Software Version 2023R1

ANSYS Inc. develops and markets engineering simulation software and services used in the aerospace, automotive, manufacturing, electronics, biomedical, energy, defense, and many other industries. ANSYS is dedicated to engineering simulation and is the world’s leading software provider. ANSYS was founded in 1970 and is headquartered in Canonsburg, Pennsylvania. ANSYS provides an engineering analysis tool combining structural, thermal, computational fluid dynamics, acoustic, and electromagnetic simulation capabilities. ANSYS has two main programs, which use the same solvers: (1) Mechanical APDL (ANSYS Design Parametric Language), a Fortran-based coding platform, and (2) ANSYS Workbench, which uses a graphical user interface to aid in finite element analysis implementation. This plan covers both APDL and Workbench. The ANSYS computer program is a large-scale, multipurpose finite element program that can be used to solve several classes of engineering analyses. The analysis capabilities of ANSYS include the ability to solve static and dynamic structural analyses, steady-state and transient heat transfer problems, mode-frequency and buckling eigenvalue problems, static or time-varying magnetic analyses, and various types of field and coupled-field applications. The program contains many special features that allow nonlinearities or secondary effects such as plasticity, large strain, hyperelasticity, creep, swelling, large deflections, contact, stress stiffening, temperature dependency, material anisotropy, and radiation to be included in the solution. As ANSYS has been developed, other special capabilities such as substructuring, submodeling, random vibration, kinetostatics, kinetodynamics, free convection fluid analysis, acoustics, magnetics, piezoelectrics, coupled-field analysis, and design optimization have been added to the program. These capabilities contribute further to making ANSYS a multipurpose analysis tool for varied engineering disciplines. The ANSYS program has been in commercial use for over 50 years and has been used extensively in the aerospace, automotive, construction, electronic, energy services, manufacturing, nuclear, plastics, oil, and steel industries. Additionally, many consulting firms and hundreds of universities have used ANSYS for analysis, research, and educational purposes. ANSYS is recognized worldwide as one of the most widely used and capable programs of its type. Ansys design analysis software is the first created within a quality system with ISO 9001 certification, the internationally accepted quality standard. Product development, testing, maintenance and support processes also meet the United States Nuclear Regulatory Commission's quality requirements, as they have for nearly four decades. The Quality Assurance Service Agreement is suitable for the customers working in the nuclear industry who need to meet specific federal regulations including 10CRF50 Appendix B and provisions of 10CFR21. ANSYS has retained its original International Organization for Standardization (ISO) 9001 accreditation certificate since1995-05-04, It’s current certificate is valid until 2027-05-29.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Unravelling Microstructure Selection in an Additively Manufactured Eutectic High‐Entropy Alloy

High-entropy alloys (HEAs) are promising candidates for advanced structural applications due to their excellent mechanical properties. Additive manufacturing (AM), with its rapid solidification conditions, enables the creation of unique nonequilibrium microstructures. To fully leverage the synergy between AM and HEAs, understanding how processing affects structure and properties is essential. Here, how solidification rate influences microstructure evolution and phase transformation pathway in laser additively manufactured AlCrFe2Ni2 eutectic HEAs is investigated. By increasing the laser scan speed and hence the solidification rate, distinct solidification modes evolving from coupled eutectic to anomalous eutectic and eventually to single-phase solidification are revealed. These transitions result in distinct microstructures and a wide range of mechanical properties. Thermodynamic modeling and molecular dynamics simulations reveal that low cooling rates allow for sufficient atomic diffusion and phase separation, facilitating coupled eutectic growth. In contrast, rapid cooling suppresses diffusion and destabilizes the solid–liquid interface, promoting anomalous or single-phase solidification. This integrated experimental and computational approach provides a multiscale understanding of solidification mechanisms in HEAs and underscores how kinetic effects can over-ride thermodynamic predictions under nonequilibrium conditions. Furthermore, these results demonstrate that AM can serve as a powerful tool to design HEAs with tailored microstructures and properties.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Numerical Prediction of Oscillation Behaviors of a Multiphase Core–Shell Droplet During Interfacial Tension Measurement

Interfacial tension between molten high-temperature materials is to be measured using the electrostatic levitation furnace (ELF) and the electromagnetic levitator (ISS-EML) aboard the International Space Station. A levitated compound droplet of a concentric core–shell structure is excited either by an impulsive electromagnetic field or by a superimposed electrostatic field. The oscillation behavior of the compound droplet is analyzed to measure interfacial tension at the interface of the two phases. In support of the space experiments, a computational fluid dynamic model was developed to characterize the oscillation behavior of multiphase core–shell droplet. The developed model predicted the interfacial tension between molten copper-rich and cobalt-rich phases with a difference of 3.3 pct compared to the values reported in literature. The developed model is being utilized to investigate the influence of various test parameters on measured surface tension and also being extended for molten steel–molten slag systems.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Full spectrum optical constant interface to the Materials Project

Optical constants characterize the interaction of materials with light and are important properties in material design. Here we present a Python-based Corvus workflow for simulations of full spectrum optical constants from the visible and ultraviolet to hard x-ray wavelengths based on the real-space Green’s function code FEFF10 and structural data from the Materials Project (MP). The Corvus workflow manager and its associated tools provide an interface to FEFF10 and the MP database. The workflow parallelizes the FEFF computations of optical constants over all absorption edges for each material in the MP database specified by a unique MP-ID. The workflow tools determine the distribution of computational resources needed for that case. Similarly, the optical constants for selected sets of materials can be computed in a single-shot. Additionally, to illustrate the approach, we present results for several elemental solids in the periodic table, as well as a sample compound, and compare our predictions with experimental results. In addition, we provide a database of calculated results for all elements for which there is a stable elemental solid at standard conditions available in the Materials Project database. As in x-ray absorption spectra, these results are interpreted in terms of an atomic-like background and fine-structure contributions.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Effect of cell compression on the performance and the structure of proton exchange membrane water electrolyzer (PEMWE) assembly

Here, in the field of water electrolysis, the proton exchange membrane water electrolyzer (PEMWE) is currently the most advanced technology for producing hydrogen without emitting CO 2 . Although PEMWE plants are already in operation, further research is needed to improve cell efficiency and reduce the use of rare materials, such as iridium oxide catalysts for the oxygen evolution reaction (OER). One of the main causes of performance loss in PEMWE is the relatively low electric conductivity of the porous transport layer (PTL) and of the anode catalyst layer, which results in ohmic losses and low catalyst utilization during high current density operation. The objective of this study is to investigate how optimization of the PTL and electrode interface can increase the cell performance. To this end, we tested different cell assemblies using fibrous and sintered PTLs, decreasing membrane thickness, reducing iridium loading, and inserting a microporous layer to increase contact surface area. Electrochemical characterization of each cell configuration was systematically performed at various compression levels as the pressure is a crucial parameter influencing the electrode/PTL contact area. In parallel, X-ray microcomputed tomography (micro-CT) was employed to investigate the effects of cell hydration and compression on the structure of PEMWE components. This study combining electrochemistry and micro-CT imaging presents how optimizing the electrode/PTL contact surface area, minimizes ohmic losses, and enables PEMWE operation with low iridium loading at high current densities.

Catalyst - PTL interface↗
DOE OSTI2025

Directed energy deposition of functionally graded V-4Cr-4Ti to Fe-9Cr transition for fusion power systems

This study proposes a graded structure via additive manufacturing for divertor and first wall blanket applications in fusion reactors. Materials were selected based on thermodynamic calculations to operate from 1100 °C at the plasma-facing level to 550 °C at the structural steel level. Conventional joining methods often lead to failures due to discrete reaction layers with significant mechanical property differences. Using laser beam-directed energy deposition (LB-DED), this study demonstrates the fabrication of a VCrTi-Gr91 steel functionally graded component through a novel process parameter optimization framework. A systematic approach included powder characterization, single-track depositions, and construction of printability maps. Near full-density specimens of each interlayer were additively manufactured, and a transition from V-based alloys to reduced activation ferritic martensitic steels was achieved. Computational material selection of interlayer alloys and thermodynamic/diffusion kinetics simulations prevented most interface incompatibilities. A brittle intermetallic formed at one interface, causing cracking, which was not predicted by current thermodynamic models. Transition alloy design approach was updated with a more recent database and a mitigation strategy has been proposed to eliminate the formation of deleterious intermetallic phases. Ultimately, LB-DED has proven effective for producing multi-material graded systems for fusion applications, with the demonstrated process parameter optimization framework applicable to various materials.

Additive manufacturing↗
DOE OSTI2017

Clinical applications of 3-dimensional printing in radiation therapy

Three-dimensional (3D) printing is suitable for the fabrication of complex radiotherapy bolus. Although investigated from dosimetric and feasibility standpoints, there are few reports to date of its use for actual patient treatment. This study illustrates the versatile applications of 3D printing in clinical radiation oncology through a selection of patient cases, namely, to create bolus for photon and modulated electron radiotherapy (MERT), as well as applicators for surface high-dose rate (HDR) brachytherapy. Photon boluses were 3D-printed to treat a recurrent squamous cell carcinoma (SCC) of the nasal septum and a basal cell carcinoma (BCC) of the posterior pinna. For a patient with a mycosis fungoides involving the upper face, a 3D-printed MERT bolus was used. To treat an SCC of the nose, a 3D-printed applicator for surface brachytherapy was made. The structures' fit to the anatomy and the radiotherapy treatment plans were assessed. Based on the treatment planning computed tomography (CT), the size of the largest air gap at the interface of the 3D-printed structure was 3 mm for the SCC of the nasal septum, 3 mm for the BCC of the pinna, 2 mm for the mycosis fungoides of the face, and 2 mm for the SCC of the nose. Acceptable treatment plans were obtained for the SCC of the nasal septum (95% isodose to 99.8% of planning target volume [PTV]), the BCC of the pinna (95% isodose to 97.7% of PTV), and the mycosis fungoides of the face (90% isodose to 92.5% of PTV). For the latter, compared with a plan with a uniform thickness bolus, the one featuring the MERT bolus achieved relative sparing of all the organs at risk (OARs) distal to the target volume, while maintaining similar target volume coverage. The surface brachytherapy plan for the SCC of the nose had adequate coverage (95% isodose to 95.6% of clinical target volume [CTV]), but a relatively high dose to the left eye, owing to its proximity to the tumor. 3D printing can be implemented effectively in the clinical setting to create highly conformal bolus for photon and MERT, as well as applicators for surface brachytherapy.

61 RADIATION PROTECTION AND DOSIMETRY↗